docstr: Activate the validation loop for the pl.LightningModule.
docstr_tok: ["Activate","the","validation","loop","for","the","pl.LightningModule","."]
code: def validation_step(self, batch, batch_idx, dataloader_idx=0):
      """
      Activate the validation loop for the pl.LightningModule.
  
      """
  
      if isinstance(batch[0], list):
          x = torch.cat([x for x, y, _ in batch])
          y = torch.cat([y for x, y, _ in batch])
      else:
          x = batch[0]
          y = batch[1]
  
      out = self.model(x)
      loss = F.cross_entropy(out, y)
      acc = (torch.argmax(out, dim=1) == y).float().mean()
  
      metrics = {"val_acc": acc, "val_loss": loss}
      self.log_dict(
          metrics, on_step=False, on_epoch=True, prog_bar=True
      )
  
file_path: dowhy/dowhy/causal_prediction/algorithms/base_algorithm.py
imports: import pytorch_lightning
  import torch
  from torch.nn import functional
label_desc: Use image node_id 3 for calling the PredictionAlgorithm obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx, dataloader_idx) without return types